Director, Cheminformatics - Modeling & Informatics

Job Description

Director, Cheminformatics – Modeling & Informatics

The successful candidate will bring exceptional matrix leadership and managerial skills to drive cheminformatics and data science innovation that amplifies pipeline impact across our discovery organization. They will lead a team of highly skilled cheminformatics professionals and create an environment that supports the growth of data science talent through sustained engagement with stakeholders in chemistry, biology, and IT.

In this role, the candidate will guide the development and application of cheminformatics capabilities that enable and enhance decision-making across the drug discovery process. The team serves as a force multiplier—translating key scientific questions into scalable data architectures, workflows, and algorithmic innovations that are broadly deployed across programs.

They will partner closely with stakeholders to ensure optimal use of resources and platforms provided by our research division's IT department, and to embed cheminformatics solutions into the DMTA cycle. Through active participation in cross-functional and cross-divisional data science communities, they will help shape and advance a data-fluent culture across the organization.

As a people manager, the successful candidate will demonstrate a passion for talent development and foster a diverse, inclusive, and high-performing team culture that empowers individuals and strengthens collaboration across sites.

Responsibilities

• Sets vision and strategy for cheminformatics capabilities and platforms that accelerate scientific learning and decision-making in drug discovery

• Leads a multi-site team of cheminformatics and data science specialists, spanning data engineering, analytics, and scientific software development

• Actively develops talent, fosters diversity of thought, and builds an inclusive culture that engages and empowers all team members

• Engages stakeholders across the drug discovery spectrum—from early target identification and chemical biology through lead optimization and safety—to understand needs and enable impactful solutions

• Translates scientific challenges into scalable data architectures, workflows, and algorithmic approaches that can be broadly leveraged across multiple projects

• Drives development of next-generation cheminformatics workflows through integration of modern technologies, including machine learning (e.g., generative and predictive modeling), knowledge graphs, and emerging AI approaches

• Ensures that developed capabilities are effectively deployed and adopted in collaboration with project teams and modeling partners

• Builds and maintains strong partnerships with IT to co-develop robust, sustainable platforms supporting scientific workflows

• Balances strategic investment in new capabilities with effective utilization of existing solutions to maximize organizational value

• Collaborates with leaders across Bioinformatics, Biostatistics, Quantitative Biology, and Modeling to align on data science strategy and priorities

• Contributes to cross-divisional alignment on the role of data science and informatics in the organization

• Works closely with Modeling, Structure, and Biophysics leadership to identify opportunities where cheminformatics can enhance broader modeling and discovery efforts

• Maintains visibility across the discovery portfolio to identify emerging needs and opportunities for scalable cheminformatics support

Education Requirements

• BS, MS or PhD in cheminformatics, bioinformatics, chemistry, biology, biochemistry, physics, statistics, computational chemistry, computational biology, data science, AI/ML, computer science, math, pharmaceutical sciences, engineering, or a related STEM field

Required Experience and Skills

• PhD and 7+ years of professional experience applying computational and data science approaches to interdisciplinary scientific problems in drug discovery, MS and 9+ years of experience, OR BS and 13+ years of experience.

• 2+ years of managerial experience with demonstrated strength in team building, talent development, and inclusive leadership

• Experience designing and implementing modern computational workflows, including coding best practices, cloud-based systems, and MLOps/DataOps approaches

• Strong understanding of cheminformatics, data analytics, and data engineering in the context of early drug discovery

• Experience enabling predictive modeling and advanced analytical approaches in a collaborative, matrixed environment

• Demonstrated ability to collaborate ac